Policymakers' and healthcare providers' perspectives on the introduction of oral pre-exposure prophylaxis for key populations in Ghana
Bibliographic record
Abstract
Abstract Background Key populations (KPs) such as female sex workers (FSWs), men who have sex with men (MSM), people who inject drugs (PWID), and their partners contribute more than a quarter (27.5%) of new HIV infection in Ghana. Oral pre-exposure prophylaxis (PrEP) can substantially reduce HIV acquisition among this group. While the available research indicates KPs willingness to take PrEP in Ghana, little is known about the position of policymakers and healthcare providers on the introduction of PrEP for KPs. Methods Qualitative data were collected from September to October 2017 in the Greater Accra (GA) and Brong-Ahafo (BA) regions of Ghana. Key informant interviews were conducted with 20 regional and national policymakers and supplemented with In-depth Interviews with 23 healthcare providers to explore their level of support for PrEP and their perspectives on challenges and issues to consider for oral PrEP implementation in Ghana. Thematic content analysis was used to unearth the issues emerging from the interviews. Results Policymakers and healthcare providers in both regions expressed strong support for introducing PrEP for KPs. Key concerns regarding oral PrEP introduction included potential for behavioral disinhibition, non-adherence and side effects of medication, cost and long-term financial implications, and stigma related to HIV and key populations. Participants stressed the need to integrate PrEP into existing services and the provision of PrEP should start with high risk groups like sero-discordant couples, FSWs and MSM. Conclusions Policymakers and providers recognize the value of PrEP in cubing new HIV infections but have concerns about disinhibition, non-adherence, and cost. Therefore, the Ghana health service should roll-out a range of strategies to address their concerns including: sensitization with providers to mitigate underlying stigma towards KPs, particularly MSM, integration of PrEP into existing services, and innovative strategies to improve continued use of PrEP.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".